Transcriptional Regulation of Human Gene Coexpression Network

Increasing variety of molecular networks emerge from high-throughput genome data. In eukaryote, transcription factor is a major regulator at transcription level. Examining relations between features of these networks and their biological significance attracts attention of many researchers. While abundant quantity of studies represented connections between protein networks and topological parameters, few approaches have been applied to transcriptional regulations of coexpression gene networks. Here, we focus on the correlation between gene features in coexpression network and the number of transcription factors regulating each gene. Networks were constructed by ARACNE algorithm using HapMap gene expression data from four human populations. Three topological characteristics (node degree, betweenness centrality and pairwise disconnectivity) were used to analyze the correlation. We show that in human coexpression gene networks, degree centrality, betweenness centrality and pairwise disconnectivity is significantly correlated with according transcription factor number. Our study provides new evidence for global correlation between transcription factor regulation and gene coexpression network topology.